Publisher
source

R Purshouse

8 months ago

EngD: Enhancing Productivity in Manufacturing Through Automation and Autonomy in Computer Aided Process Planning (Sponsored by Boeing) University of Sheffield in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Sheffield

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Keywords

Computer Science
Data Science
Machine Learning
Systems Engineering
Mechanical Engineering
Materials Science
Aerospace Engineering
Mathematics
Artificial Intelligence
Mathematical Modeling
Manufacturing Engineering
Industrial Engineering
Software Engineering
Automation
Computational Mathematics
Device Engineering
Autonomy
Optimisation
Robotics
Control System

About this position

This EngD project, sponsored by Boeing, offers a unique opportunity to advance productivity in manufacturing through the development of automation and autonomy in computer-aided process planning. Manufacturing process planning involves numerous inter-related decisions, often managed manually and varying significantly between manufacturers. The project aims to streamline these processes by integrating multiple manufacturing data sources, enabling more efficient decision-making and reducing repetitive, labour-intensive tasks. This will allow engineers to focus on complex, value-added activities.

The research aligns with the Autonomous Tool Room (ATR) initiative, which encompasses three pillars: autonomous machining environments, data-centric repositories, and autonomous process planning. Your work will directly contribute to the autonomous process planning pillar, focusing on leveraging all available datasets to create optimal, transparent process flows. You will explore methods for manufacturing engineers to assess and utilize historical data for continuous improvement, and develop systems that learn and adapt by identifying patterns and trends.

As a student in this project, you will make a significant impact on the manufacturing sector by creating a user-friendly optimization tool accessible to engineers regardless of prior experience. The project is embedded within the EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing at the University of Sheffield, providing access to world-class facilities and expertise in machining, assembly, and digital engineering.

Benefits include a fully-funded four-year postgraduate research degree (EngD or PhD) with an annual tax-free stipend of £28,000, equivalent to a £34,000 salary. You will also receive a £35,000 research training support grant over four years for equipment, conference travel, and project consumables. The program offers tailored training, support for Chartered Engineer (CEng) status, and opportunities to collaborate with industry leaders on real-world projects. Graduates from this CDT have secured senior roles in top industries, thanks to the hands-on experience and industry connections developed during their studies.

Eligibility is open to both UK and international students. Applicants should hold a first-class or strong 2:1 degree in a relevant science or engineering discipline, such as Mechanical Engineering, Aerospace Engineering, Materials Science, Physics, Computer Science, Systems Engineering, Robotics, or Mechatronics. Non-native English speakers must demonstrate proficiency with an IELTS score of 6.5 overall and at least 6.0 in each section. UK Home students must have no restrictions on stay and have been ordinarily resident in the UK for at least three years prior to the scholarship.

To apply, familiarize yourself with the MADE4 Manufacturing CDT website and follow the University of Sheffield admissions process. Select 'Doctoral Training Course' and 'MADE4 Manufacturing CDT' as your course, choosing either EngD or PhD. Submit transcripts, degree certificates, CV, personal statement, and evidence of English language ability if applicable. The application deadline is March 15, 2026.

For further information, contact [email protected] or visit www.sheffield.ac.uk/made4manufacturing.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants must have a first-class or strong 2:1 degree in a relevant science or engineering subject such as Mechanical Engineering, Aerospace Engineering, Materials Science, Physics, Computer Science, Systems Engineering, Robotics, or Mechatronics. If English is not the applicant's first language, an overall IELTS score of 6.5 with at least 6.0 in each section is required. Eligibility is open to Home (UK) and International students; UK Home students must have no restrictions on stay and have been ordinarily resident in the UK for at least 3 years prior to the scholarship start.

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Professors

Prof at EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing

University Name
Country flag

United Kingdom

Research Interests

Artificial Intelligence

Aerospace Engineering

Materials Science

Mathematical Modeling

Optimisation